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How to estimate expected credit losses – ECL – for provisioning under IFRS 9

Mariya Gubareva (ISCAL - Lisbon Accounting and Business School, Instituto Politécnico de Lisboa, Lisbon, Portugal) (SOCIUS/CSG - Research in Social Sciences and Management, Lisbon, Portugal)

Journal of Risk Finance

ISSN: 1526-5943

Article publication date: 3 June 2021

Issue publication date: 29 June 2021

739

Abstract

Purpose

This paper provides an objective approach based on available market information capable of reducing subjectivity, inherently present in the process of expected loss provisioning under the IFRS 9.

Design/methodology/approach

This paper develops the two-step methodology. Calibrating the Credit Default Swap (CDS)-implied default probabilities to the through-the-cycle default frequencies provides average weights of default component in the spread for each forward term. Then, the impairment provisions are calculated for a sample of investment grade and high yield obligors by distilling their pure default-risk term-structures from the respective term-structures of spreads. This research demonstrates how to estimate credit impairment allowances compliant with IFRS 9 framework.

Findings

This study finds that for both investment grade and high yield exposures, the weights of default component in the credit spreads always remain inferior to 33%. The research's outcomes contrast with several previous results stating that the default risk premium accounts at least for 40% of CDS spreads. The proposed methodology is applied to calculate IFRS 9 compliant provisions for a sample of investment grade and high yield obligors.

Research limitations/implications

Many issuers are not covered by individual Bloomberg valuation curves. However, the way to overcome this limitation is proposed.

Practical implications

The proposed approach offers a clue for a better alignment of accounting practices, financial regulation and credit risk management, using expected loss metrics across diverse silos inside organizations. It encourages adopting the proposed methodology, illustrating its application to a set of bond exposures.

Originality/value

No previous research addresses impairment provisioning employing Bloomberg valuation curves. The study fills this gap.

Keywords

Acknowledgements

This work was supported by FCT, I.P., the Portuguese national funding agency for science, research and technology, under the Project UIDB/04521/2020, and by Instituto Politécnico de Lisboa as a part of the IPL/2020/MacroRates/ISCAL project.

Citation

Gubareva, M. (2021), "How to estimate expected credit losses – ECL – for provisioning under IFRS 9", Journal of Risk Finance, Vol. 22 No. 2, pp. 169-190. https://doi.org/10.1108/JRF-05-2020-0094

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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